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» When to Update the sequential patterns of stream data
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VLDB
1999
ACM
188views Database» more  VLDB 1999»
13 years 11 months ago
SPIRIT: Sequential Pattern Mining with Regular Expression Constraints
Discovering sequential patterns is an important problem in data mining with a host of application domains including medicine, telecommunications, and the World Wide Web. Conventio...
Minos N. Garofalakis, Rajeev Rastogi, Kyuseok Shim
ADC
2008
Springer
156views Database» more  ADC 2008»
14 years 1 months ago
Interactive Mining of Frequent Itemsets over Arbitrary Time Intervals in a Data Stream
Mining frequent patterns in a data stream is very challenging for the high complexity of managing patterns with bounded memory against the unbounded data. While many approaches as...
Ming-Yen Lin, Sue-Chen Hsueh, Sheng-Kun Hwang
DMSN
2004
ACM
14 years 4 days ago
Predictive filtering: a learning-based approach to data stream filtering
Recent years have witnessed an increasing interest in filtering of distributed data streams, such as those produced by networked sensors. The focus is to conserve bandwidth and se...
Vibhore Kumar, Brian F. Cooper, Shamkant B. Navath...
ICDE
2005
IEEE
176views Database» more  ICDE 2005»
14 years 9 days ago
LAPIN-SPAM: An Improved Algorithm for Mining Sequential Pattern
Sequence pattern mining is an important research problem because it is the basis of many other applications. Yet how to efficiently implement the mining is difficult due to the ...
Zhenglu Yang, Masaru Kitsuregawa
PAKDD
2007
ACM
144views Data Mining» more  PAKDD 2007»
14 years 25 days ago
Approximately Mining Recently Representative Patterns on Data Streams
Catching the recent trend of data is an important issue when mining frequent itemsets from data streams. To prevent from storing the whole transaction data within the sliding windo...
Jia-Ling Koh, Yuan-Bin Don